Here home_court is constant across all teams, and the product of all the team_home_court factors equals 1.

The overall impact on a team will be team_home_court_offense/team_home_court_defense.

Here are the separate offensive and defensive HCA values for each team. Above 1.0 is positive for offense (you score more points at home than a typical team) and below 1.0 is positive for defense (you allow fewer points at home than a typical team).

I'm pooling data across 2002-2013; I should have made that clear. Of course, home court advantage could shift from year to year - this is a topic worthy of much more detailed study, but it's clear there's a gigantic impact.

I could easily geocode arena locations and include distance traveled in my model, but I'd need a list of arena locations by team by year.

Road disadvantage would be confounded by strength of team offense and defense in the presence of home advantage factors. You'd need to escalate to team strength estimates based on players in order to estimate road disadvantage.